Method and apparatus for video coding

ABSTRACT

Aspects of the disclosure provide methods and apparatuses for video processing. In some examples, an apparatus for video processing includes processing circuitry. The processing circuitry converts a picture in a subsampled format in a color space into a non subsampled format in the color space. Then, the processing circuitry clips values of a color component of the picture in the non subsampled format before providing the picture in the non subsampled format as an input to a neural network based filter.

INCORPORATION BY REFERENCE

This present application claims the benefit of priority to U.S.Provisional Application No. 63/131,656, APPLICATION OF CLIPPING TOIMPROVE PRE-PROCESSING IN A NEURAL NETWORK BASED IN-LOOP FILTER IN AVIDEO CODEC” filed on Dec. 29, 2020, which is incorporated by referenceherein in its entirety.

TECHNICAL FIELD

The present disclosure describes embodiments generally related to videocoding. More specifically, the present disclosure provides techniquesfor improving neural network based in loop filter.

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent the work is described in thisbackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

Video coding and decoding can be performed using inter-pictureprediction with motion compensation. Uncompressed digital video caninclude a series of pictures, each picture having a spatial dimensionof, for example, 1920×1080 luminance samples and associated chrominancesamples. The series of pictures can have a fixed or variable picturerate (informally also known as frame rate), of, for example 60 picturesper second or 60 Hz. Uncompressed video has specific bitraterequirements. For example, 1080p60 4:2:0 video at 8 bit per sample(1920×1080 luminance sample resolution at 60 Hz frame rate) requiresclose to 1.5 Gbit/s bandwidth. An hour of such video requires more than600 GBytes of storage space.

One purpose of video coding and decoding can be the reduction ofredundancy in the input video signal, through compression. Compressioncan help reduce the aforementioned bandwidth and/or storage spacerequirements, in some cases by two orders of magnitude or more. Bothlossless compression and lossy compression, as well as a combinationthereof can be employed. Lossless compression refers to techniques wherean exact copy of the original signal can be reconstructed from thecompressed original signal. When using lossy compression, thereconstructed signal may not be identical to the original signal, butthe distortion between original and reconstructed signals is smallenough to make the reconstructed signal useful for the intendedapplication. In the case of video, lossy compression is widely employed.The amount of distortion tolerated depends on the application; forexample, users of certain consumer streaming applications may toleratehigher distortion than users of television distribution applications.The compression ratio achievable can reflect that: higherallowable/tolerable distortion can yield higher compression ratios.

A video encoder and decoder can utilize techniques from several broadcategories, including, for example, motion compensation, transform,quantization, and entropy coding.

Video codec technologies can include techniques known as intra coding.In intra coding, sample values are represented without reference tosamples or other data from previously reconstructed reference pictures.In some video codecs, the picture is spatially subdivided into blocks ofsamples. When all blocks of samples are coded in intra mode, thatpicture can be an intra picture. Intra pictures and their derivationssuch as independent decoder refresh pictures, can be used to reset thedecoder state and can, therefore, be used as the first picture in acoded video bitstream and a video session, or as a still image. Thesamples of an intra block can be exposed to a transform, and thetransform coefficients can be quantized before entropy coding. Intraprediction can be a technique that minimizes sample values in thepre-transform domain. In some cases, the smaller the DC value after atransform is, and the smaller the AC coefficients are, the fewer thebits that are required at a given quantization step size to representthe block after entropy coding.

Traditional intra coding such as known from, for example MPEG-2generation coding technologies, does not use intra prediction. However,some newer video compression technologies include techniques thatattempt, from, for example, surrounding sample data and/or metadataobtained during the encoding/decoding of spatially neighboring, andpreceding in decoding order, blocks of data. Such techniques arehenceforth called “intra prediction” techniques. Note that in at leastsome cases, intra prediction is using reference data only from thecurrent picture under reconstruction and not from reference pictures.

There can be many different forms of intra prediction. When more thanone of such techniques can be used in a given video coding technology,the technique in use can be coded in an intra prediction mode. Incertain cases, modes can have submodes and/or parameters, and those canbe coded individually or included in the mode codeword. Which codewordto use for a given mode/submode/parameter combination can have an impactin the coding efficiency gain through intra prediction, and so can theentropy coding technology used to translate the codewords into abitstream.

A certain mode of intra prediction was introduced with H.264, refined inH.265, and further refined in newer coding technologies such as jointexploration model (JEM), versatile video coding (VVC), and benchmark set(BMS). A predictor block can be formed using neighboring sample valuesbelonging to already available samples. Sample values of neighboringsamples are copied into the predictor block according to a direction. Areference to the direction in use can be coded in the bitstream or mayitself be predicted.

Referring to FIG. 1A, depicted in the lower right is a subset of ninepredictor directions known from H.265's 33 possible predictor directions(corresponding to the 33 angular modes of the 35 intra modes). The pointwhere the arrows converge (101) represents the sample being predicted.The arrows represent the direction from which the sample is beingpredicted. For example, arrow (102) indicates that sample (101) ispredicted from a sample or samples to the upper right, at a 45 degreeangle from the horizontal. Similarly, arrow (103) indicates that sample(101) is predicted from a sample or samples to the lower left of sample(101), in a 22.5 degree angle from the horizontal.

Still referring to FIG. 1A, on the top left there is depicted a squareblock (104) of 4×4 samples (indicated by a dashed, boldface line). Thesquare block (104) includes 16 samples, each labelled with an “S”, itsposition in the Y dimension (e.g., row index) and its position in the Xdimension (e.g., column index). For example, sample S21 is the secondsample in the Y dimension (from the top) and the first (from the left)sample in the X dimension. Similarly, sample S44 is the fourth sample inblock (104) in both the Y and X dimensions. As the block is 4×4 samplesin size, S44 is at the bottom right. Further shown are reference samplesthat follow a similar numbering scheme. A reference sample is labelledwith an R, its Y position (e.g., row index) and X position (columnindex) relative to block (104). In both H.264 and H.265, predictionsamples neighbor the block under reconstruction; therefore no negativevalues need to be used.

Intra picture prediction can work by copying reference sample valuesfrom the neighboring samples as appropriated by the signaled predictiondirection. For example, assume the coded video bitstream includessignaling that, for this block, indicates a prediction directionconsistent with arrow (102)—that is, samples are predicted from aprediction sample or samples to the upper right, at a 45 degree anglefrom the horizontal. In that case, samples S41, S32, S23, and S14 arepredicted from the same reference sample R05. Sample S44 is thenpredicted from reference sample R08.

In certain cases, the values of multiple reference samples may becombined, for example through interpolation, in order to calculate areference sample; especially when the directions are not evenlydivisible by 45 degrees.

The number of possible directions has increased as video codingtechnology has developed. In H.264 (year 2003), nine different directioncould be represented. That increased to 33 in H.265 (year 2013), andJEM/VVC/BMS, at the time of disclosure, can support up to 65 directions.Experiments have been conducted to identify the most likely directions,and certain techniques in the entropy coding are used to represent thoselikely directions in a small number of bits, accepting a certain penaltyfor less likely directions. Further, the directions themselves cansometimes be predicted from neighboring directions used in neighboring,already decoded, blocks.

FIG. 1B shows a schematic (180) that depicts 65 intra predictiondirections according to JEM to illustrate the increasing number ofprediction directions over time.

The mapping of intra prediction directions bits in the coded videobitstream that represent the direction can be different from videocoding technology to video coding technology; and can range, forexample, from simple direct mappings of prediction direction to intraprediction mode, to codewords, to complex adaptive schemes involvingmost probable modes, and similar techniques. In all cases, however,there can be certain directions that are statistically less likely tooccur in video content than certain other directions. As the goal ofvideo compression is the reduction of redundancy, those less likelydirections will, in a well working video coding technology, berepresented by a larger number of bits than more likely directions.

Motion compensation can be a lossy compression technique and can relateto techniques where a block of sample data from a previouslyreconstructed picture or part thereof (reference picture), after beingspatially shifted in a direction indicated by a motion vector (MVhenceforth), is used for the prediction of a newly reconstructed pictureor picture part. In some cases, the reference picture can be the same asthe picture currently under reconstruction. MVs can have two dimensionsX and Y, or three dimensions, the third being an indication of thereference picture in use (the latter, indirectly, can be a timedimension).

In some video compression techniques, an MV applicable to a certain areaof sample data can be predicted from other MVs, for example from thoserelated to another area of sample data spatially adjacent to the areaunder reconstruction, and preceding that MV in decoding order. Doing socan substantially reduce the amount of data required for coding the MV,thereby removing redundancy and increasing compression. MV predictioncan work effectively, for example, because when coding an input videosignal derived from a camera (known as natural video) there is astatistical likelihood that areas larger than the area to which a singleMV is applicable move in a similar direction and, therefore, can in somecases be predicted using a similar motion vector derived from MVs ofneighboring area. That results in the MV found for a given area to besimilar or the same as the MV predicted from the surrounding MVs, andthat in turn can be represented, after entropy coding, in a smallernumber of bits than what would be used if coding the MV directly. Insome cases, MV prediction can be an example of lossless compression of asignal (namely: the MVs) derived from the original signal (namely: thesample stream). In other cases, MV prediction itself can be lossy, forexample because of rounding errors when calculating a predictor fromseveral surrounding MVs.

Various MV prediction mechanisms are described in H.265/HEVC (ITU-T Rec.H.265, “High Efficiency Video Coding”, December 2016). Out of the manyMV prediction mechanisms that H.265 offers, described here is atechnique henceforth referred to as “spatial merge”.

Referring to FIG. 2 , a current block (201) comprises samples that havebeen found by the encoder during the motion search process to bepredictable from a previous block of the same size that has beenspatially shifted. Instead of coding that MV directly, the MV can bederived from metadata associated with one or more reference pictures,for example from the most recent (in decoding order) reference picture,using the MV associated with either one of five surrounding samples,denoted A0, A1, and B0, B1, B2 (202 through 206, respectively). InH.265, the MV prediction can use predictors from the same referencepicture that the neighboring block is using.

SUMMARY

Aspects of the disclosure provide methods and apparatuses for videoprocessing. In some examples, an apparatus for video processing includesprocessing circuitry. The processing circuitry converts a picture in asubsampled format in a color space into a non subsampled format in thecolor space. Then, the processing circuitry clips values of a colorcomponent of the picture in the non subsampled format before providingthe picture in the non subsampled format as an input to a neural networkbased filter.

In some examples, the processing circuitry clips the values of the colorcomponent of the picture in the non subsampled format into a valid rangefor the color component. In an example, the processing circuitry clipsthe values of the color component of the picture in the non subsampledformat into a range that is determined based on a bitdepth. In anotherexample, the processing circuitry clips the values of the colorcomponent of the picture in the non subsampled format into a range thatis predetermined.

In some examples, the processing circuitry determines a range forclipping the values based on decoded information from a bitstream thatcarries the picture, and then clips the values of the color component ofthe picture in the non subsampled format into the determined range. Inan example, the processing circuitry decodes, from at least one of asequence parameter set, a picture parameter set, a slice header and atile header in the bitstream, a signal that is indicative of the range.

In some examples, the processing circuitry reconstructs the picture inthe subsampled format based on decoded information from a bitstream, andapplies a deblocking filter on the picture in the subsampled format. Insome examples, the processing circuitry applies the neural network basedfilter on the picture in the non subsampled format with the clippedvalues to generate a filtered picture of the non subsampled format, andconverts the filtered picture in the non subsampled format to a filteredpicture of the subsampled format.

In some examples, the picture in the non subsampled format with theclipped values is stored in a storage. Then, the stored picture in thenon subsampled format with the clipped values can be provided as atraining input to train a neural network in the neural network basedfilter.

Aspects of the disclosure also provide a non-transitorycomputer-readable medium storing instructions which when executed by acomputer for video decoding cause the computer to perform the method forvideo processing.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features, the nature, and various advantages of the disclosedsubject matter will be more apparent from the following detaileddescription and the accompanying drawings in which:

FIG. 1A is a schematic illustration of an exemplary subset of intraprediction modes.

FIG. 1B is an illustration of exemplary intra prediction directions.

FIG. 2 is a schematic illustration of a current block and itssurrounding spatial merge candidates in one example.

FIG. 3 is a schematic illustration of a simplified block diagram of acommunication system (300) in accordance with an embodiment.

FIG. 4 is a schematic illustration of a simplified block diagram of acommunication system (400) in accordance with an embodiment.

FIG. 5 is a schematic illustration of a simplified block diagram of adecoder in accordance with an embodiment.

FIG. 6 is a schematic illustration of a simplified block diagram of anencoder in accordance with an embodiment.

FIG. 7 shows a block diagram of an encoder in accordance with anotherembodiment.

FIG. 8 shows a block diagram of a decoder in accordance with anotherembodiment.

FIG. 9 shows a block diagram of a loop filter unit in some examples.

FIG. 10 shows a block diagram of another loop filter unit in someexamples.

FIG. 11 shows a block diagram of a neural network based filter in someexamples.

FIG. 12 shows a block diagram of a pre-processing module in someexamples.

FIG. 13 shows a block diagram of a neural network structure in someexamples.

FIG. 14 shows a block diagram of a dense residual unit.

FIG. 15 shows a block diagram of a post processing module in someexamples.

FIG. 16 shows a block diagram of a pre-processing module in someexamples.

FIG. 17 shows a flow chart outlining a process example.

FIG. 18 is a schematic illustration of a computer system in accordancewith an embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

FIG. 3 illustrates a simplified block diagram of a communication system(300) according to an embodiment of the present disclosure. Thecommunication system (300) includes a plurality of terminal devices thatcan communicate with each other, via, for example, a network (350). Forexample, the communication system (300) includes a first pair ofterminal devices (310) and (320) interconnected via the network (350).In the FIG. 3 example, the first pair of terminal devices (310) and(320) performs unidirectional transmission of data. For example, theterminal device (310) may code video data (e.g., a stream of videopictures that are captured by the terminal device (310)) fortransmission to the other terminal device (320) via the network (350).The encoded video data can be transmitted in the form of one or morecoded video bitstreams. The terminal device (320) may receive the codedvideo data from the network (350), decode the coded video data torecover the video pictures and display video pictures according to therecovered video data. Unidirectional data transmission may be common inmedia serving applications and the like.

In another example, the communication system (300) includes a secondpair of terminal devices (330) and (340) that performs bidirectionaltransmission of coded video data that may occur, for example, duringvideoconferencing. For bidirectional transmission of data, in anexample, each terminal device of the terminal devices (330) and (340)may code video data (e.g., a stream of video pictures that are capturedby the terminal device) for transmission to the other terminal device ofthe terminal devices (330) and (340) via the network (350). Eachterminal device of the terminal devices (330) and (340) also may receivethe coded video data transmitted by the other terminal device of theterminal devices (330) and (340), and may decode the coded video data torecover the video pictures and may display video pictures at anaccessible display device according to the recovered video data.

In the FIG. 3 example, the terminal devices (310), (320), (330) and(340) may be illustrated as servers, personal computers and smart phonesbut the principles of the present disclosure may be not so limited.Embodiments of the present disclosure find application with laptopcomputers, tablet computers, media players and/or dedicated videoconferencing equipment. The network (350) represents any number ofnetworks that convey coded video data among the terminal devices (310),(320), (330) and (340), including for example wireline (wired) and/orwireless communication networks. The communication network (350) mayexchange data in circuit-switched and/or packet-switched channels.Representative networks include telecommunications networks, local areanetworks, wide area networks and/or the Internet. For the purposes ofthe present discussion, the architecture and topology of the network(350) may be immaterial to the operation of the present disclosureunless explained herein below.

FIG. 4 illustrates, as an example for an application for the disclosedsubject matter, the placement of a video encoder and a video decoder ina streaming environment. The disclosed subject matter can be equallyapplicable to other video enabled applications, including, for example,video conferencing, digital TV, storing of compressed video on digitalmedia including CD, DVD, memory stick and the like, and so on.

A streaming system may include a capture subsystem (413), that caninclude a video source (401), for example a digital camera, creating forexample a stream of video pictures (402) that are uncompressed. In anexample, the stream of video pictures (402) includes samples that aretaken by the digital camera. The stream of video pictures (402),depicted as a bold line to emphasize a high data volume when compared toencoded video data (404) (or coded video bitstreams), can be processedby an electronic device (420) that includes a video encoder (403)coupled to the video source (401). The video encoder (403) can includehardware, software, or a combination thereof to enable or implementaspects of the disclosed subject matter as described in more detailbelow. The encoded video data (404) (or encoded video bitstream (404)),depicted as a thin line to emphasize the lower data volume when comparedto the stream of video pictures (402), can be stored on a streamingserver (405) for future use. One or more streaming client subsystems,such as client subsystems (406) and (408) in FIG. 4 can access thestreaming server (405) to retrieve copies (407) and (409) of the encodedvideo data (404). A client subsystem (406) can include a video decoder(410), for example, in an electronic device (430). The video decoder(410) decodes the incoming copy (407) of the encoded video data andcreates an outgoing stream of video pictures (411) that can be renderedon a display (412) (e.g., display screen) or other rendering device (notdepicted). In some streaming systems, the encoded video data (404),(407), and (409) (e.g., video bitstreams) can be encoded according tocertain video coding/compression standards. Examples of those standardsinclude ITU-T Recommendation H.265. In an example, a video codingstandard under development is informally known as Versatile Video Coding(VVC). The disclosed subject matter may be used in the context of VVC.

It is noted that the electronic devices (420) and (430) can includeother components (not shown). For example, the electronic device (420)can include a video decoder (not shown) and the electronic device (430)can include a video encoder (not shown) as well.

FIG. 5 shows a block diagram of a video decoder (510) according to anembodiment of the present disclosure. The video decoder (510) can beincluded in an electronic device (530). The electronic device (530) caninclude a receiver (531) (e.g., receiving circuitry). The video decoder(510) can be used in the place of the video decoder (410) in the FIG. 4example.

The receiver (531) may receive one or more coded video sequences to bedecoded by the video decoder (510); in the same or another embodiment,one coded video sequence at a time, where the decoding of each codedvideo sequence is independent from other coded video sequences. Thecoded video sequence may be received from a channel (501), which may bea hardware/software link to a storage device which stores the encodedvideo data. The receiver (531) may receive the encoded video data withother data, for example, coded audio data and/or ancillary data streams,that may be forwarded to their respective using entities (not depicted).The receiver (531) may separate the coded video sequence from the otherdata. To combat network jitter, a buffer memory (515) may be coupled inbetween the receiver (531) and an entropy decoder/parser (520) (“parser(520)” henceforth). In certain applications, the buffer memory (515) ispart of the video decoder (510). In others, it can be outside of thevideo decoder (510) (not depicted). In still others, there can be abuffer memory (not depicted) outside of the video decoder (510), forexample to combat network jitter, and in addition another buffer memory(515) inside the video decoder (510), for example to handle playouttiming. When the receiver (531) is receiving data from a store/forwarddevice of sufficient bandwidth and controllability, or from anisosynchronous network, the buffer memory (515) may not be needed, orcan be small. For use on best effort packet networks such as theInternet, the buffer memory (515) may be required, can be comparativelylarge and can be advantageously of adaptive size, and may at leastpartially be implemented in an operating system or similar elements (notdepicted) outside of the video decoder (510).

The video decoder (510) may include the parser (520) to reconstructsymbols (521) from the coded video sequence. Categories of those symbolsinclude information used to manage operation of the video decoder (510),and potentially information to control a rendering device such as arender device (512) (e.g., a display screen) that is not an integralpart of the electronic device (530) but can be coupled to the electronicdevice (530), as was shown in FIG. 5 . The control information for therendering device(s) may be in the form of Supplemental EnhancementInformation (SEI messages) or Video Usability Information (VUI)parameter set fragments (not depicted). The parser (520) mayparse/entropy-decode the coded video sequence that is received. Thecoding of the coded video sequence can be in accordance with a videocoding technology or standard, and can follow various principles,including variable length coding, Huffman coding, arithmetic coding withor without context sensitivity, and so forth. The parser (520) mayextract from the coded video sequence, a set of subgroup parameters forat least one of the subgroups of pixels in the video decoder, based uponat least one parameter corresponding to the group. Subgroups can includeGroups of Pictures (GOPs), pictures, tiles, slices, macroblocks, CodingUnits (CUs), blocks, Transform Units (TUs), Prediction Units (PUs) andso forth. The parser (520) may also extract from the coded videosequence information such as transform coefficients, quantizer parametervalues, motion vectors, and so forth.

The parser (520) may perform an entropy decoding/parsing operation onthe video sequence received from the buffer memory (515), so as tocreate symbols (521).

Reconstruction of the symbols (521) can involve multiple different unitsdepending on the type of the coded video picture or parts thereof (suchas: inter and intra picture, inter and intra block), and other factors.Which units are involved, and how, can be controlled by the subgroupcontrol information that was parsed from the coded video sequence by theparser (520). The flow of such subgroup control information between theparser (520) and the multiple units below is not depicted for clarity.

Beyond the functional blocks already mentioned, the video decoder (510)can be conceptually subdivided into a number of functional units asdescribed below. In a practical implementation operating undercommercial constraints, many of these units interact closely with eachother and can, at least partly, be integrated into each other. However,for the purpose of describing the disclosed subject matter, theconceptual subdivision into the functional units below is appropriate.

A first unit is the scaler/inverse transform unit (551). Thescaler/inverse transform unit (551) receives a quantized transformcoefficient as well as control information, including which transform touse, block size, quantization factor, quantization scaling matrices,etc. as symbol(s) (521) from the parser (520). The scaler/inversetransform unit (551) can output blocks comprising sample values, thatcan be input into aggregator (555).

In some cases, the output samples of the scaler/inverse transform (551)can pertain to an intra coded block; that is: a block that is not usingpredictive information from previously reconstructed pictures, but canuse predictive information from previously reconstructed parts of thecurrent picture. Such predictive information can be provided by an intrapicture prediction unit (552). In some cases, the intra pictureprediction unit (552) generates a block of the same size and shape ofthe block under reconstruction, using surrounding already reconstructedinformation fetched from the current picture buffer (558). The currentpicture buffer (558) buffers, for example, partly reconstructed currentpicture and/or fully reconstructed current picture. The aggregator(555), in some cases, adds, on a per sample basis, the predictioninformation the intra prediction unit (552) has generated to the outputsample information as provided by the scaler/inverse transform unit(551).

In other cases, the output samples of the scaler/inverse transform unit(551) can pertain to an inter coded, and potentially motion compensatedblock. In such a case, a motion compensation prediction unit (553) canaccess reference picture memory (557) to fetch samples used forprediction. After motion compensating the fetched samples in accordancewith the symbols (521) pertaining to the block, these samples can beadded by the aggregator (555) to the output of the scaler/inversetransform unit (551) (in this case called the residual samples orresidual signal) so as to generate output sample information. Theaddresses within the reference picture memory (557) from where themotion compensation prediction unit (553) fetches prediction samples canbe controlled by motion vectors, available to the motion compensationprediction unit (553) in the form of symbols (521) that can have, forexample X, Y, and reference picture components. Motion compensation alsocan include interpolation of sample values as fetched from the referencepicture memory (557) when sub-sample exact motion vectors are in use,motion vector prediction mechanisms, and so forth.

The output samples of the aggregator (555) can be subject to variousloop filtering techniques in the loop filter unit (556). Videocompression technologies can include in-loop filter technologies thatare controlled by parameters included in the coded video sequence (alsoreferred to as coded video bitstream) and made available to the loopfilter unit (556) as symbols (521) from the parser (520), but can alsobe responsive to meta-information obtained during the decoding ofprevious (in decoding order) parts of the coded picture or coded videosequence, as well as responsive to previously reconstructed andloop-filtered sample values.

The output of the loop filter unit (556) can be a sample stream that canbe output to the render device (512) as well as stored in the referencepicture memory (557) for use in future inter-picture prediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future prediction. For example, once a codedpicture corresponding to a current picture is fully reconstructed andthe coded picture has been identified as a reference picture (by, forexample, the parser (520)), the current picture buffer (558) can becomea part of the reference picture memory (557), and a fresh currentpicture buffer can be reallocated before commencing the reconstructionof the following coded picture.

The video decoder (510) may perform decoding operations according to apredetermined video compression technology in a standard, such as ITU-TRec. H.265. The coded video sequence may conform to a syntax specifiedby the video compression technology or standard being used, in the sensethat the coded video sequence adheres to both the syntax of the videocompression technology or standard and the profiles as documented in thevideo compression technology or standard. Specifically, a profile canselect certain tools as the only tools available for use under thatprofile from all the tools available in the video compression technologyor standard. Also necessary for compliance can be that the complexity ofthe coded video sequence is within bounds as defined by the level of thevideo compression technology or standard. In some cases, levels restrictthe maximum picture size, maximum frame rate, maximum reconstructionsample rate (measured in, for example megasamples per second), maximumreference picture size, and so on. Limits set by levels can, in somecases, be further restricted through Hypothetical Reference Decoder(HRD) specifications and metadata for HRD buffer management signaled inthe coded video sequence.

In an embodiment, the receiver (531) may receive additional (redundant)data with the encoded video. The additional data may be included as partof the coded video sequence(s). The additional data may be used by thevideo decoder (510) to properly decode the data and/or to moreaccurately reconstruct the original video data. Additional data can bein the form of, for example, temporal, spatial, or signal noise ratio(SNR) enhancement layers, redundant slices, redundant pictures, forwarderror correction codes, and so on.

FIG. 6 shows a block diagram of a video encoder (603) according to anembodiment of the present disclosure. The video encoder (603) isincluded in an electronic device (620). The electronic device (620)includes a transmitter (640) (e.g., transmitting circuitry). The videoencoder (603) can be used in the place of the video encoder (403) in theFIG. 4 example.

The video encoder (603) may receive video samples from a video source(601) (that is not part of the electronic device (620) in the FIG. 6example) that may capture video image(s) to be coded by the videoencoder (603). In another example, the video source (601) is a part ofthe electronic device (620).

The video source (601) may provide the source video sequence to be codedby the video encoder (603) in the form of a digital video sample streamthat can be of any suitable bit depth (for example: 8 bit, 10 bit, 12bit, . . . ), any color space (for example, BT.601 Y CrCB, RGB, . . . ),and any suitable sampling structure (for example Y CrCb 4:2:0, Y CrCb4:4:4). In a media serving system, the video source (601) may be astorage device storing previously prepared video. In a videoconferencingsystem, the video source (601) may be a camera that captures local imageinformation as a video sequence. Video data may be provided as aplurality of individual pictures that impart motion when viewed insequence. The pictures themselves may be organized as a spatial array ofpixels, wherein each pixel can comprise one or more samples depending onthe sampling structure, color space, etc. in use. A person skilled inthe art can readily understand the relationship between pixels andsamples. The description below focuses on samples.

According to an embodiment, the video encoder (603) may code andcompress the pictures of the source video sequence into a coded videosequence (643) in real time or under any other time constraints asrequired by the application. Enforcing appropriate coding speed is onefunction of a controller (650). In some embodiments, the controller(650) controls other functional units as described below and isfunctionally coupled to the other functional units. The coupling is notdepicted for clarity. Parameters set by the controller (650) can includerate control related parameters (picture skip, quantizer, lambda valueof rate-distortion optimization techniques, . . . ), picture size, groupof pictures (GOP) layout, maximum motion vector search range, and soforth. The controller (650) can be configured to have other suitablefunctions that pertain to the video encoder (603) optimized for acertain system design.

In some embodiments, the video encoder (603) is configured to operate ina coding loop. As an oversimplified description, in an example, thecoding loop can include a source coder (630) (e.g., responsible forcreating symbols, such as a symbol stream, based on an input picture tobe coded, and a reference picture(s)), and a (local) decoder (633)embedded in the video encoder (603). The decoder (633) reconstructs thesymbols to create the sample data in a similar manner as a (remote)decoder also would create (as any compression between symbols and codedvideo bitstream is lossless in the video compression technologiesconsidered in the disclosed subject matter). The reconstructed samplestream (sample data) is input to the reference picture memory (634). Asthe decoding of a symbol stream leads to bit-exact results independentof decoder location (local or remote), the content in the referencepicture memory (634) is also bit exact between the local encoder andremote encoder. In other words, the prediction part of an encoder “sees”as reference picture samples exactly the same sample values as a decoderwould “see” when using prediction during decoding. This fundamentalprinciple of reference picture synchronicity (and resulting drift, ifsynchronicity cannot be maintained, for example because of channelerrors) is used in some related arts as well.

The operation of the “local” decoder (633) can be the same as of a“remote” decoder, such as the video decoder (510), which has alreadybeen described in detail above in conjunction with FIG. 5 . Brieflyreferring also to FIG. 5 , however, as symbols are available andencoding/decoding of symbols to a coded video sequence by an entropycoder (645) and the parser (520) can be lossless, the entropy decodingparts of the video decoder (510), including the buffer memory (515), andparser (520) may not be fully implemented in the local decoder (633).

An observation that can be made at this point is that any decodertechnology except the parsing/entropy decoding that is present in adecoder also necessarily needs to be present, in substantially identicalfunctional form, in a corresponding encoder. For this reason, thedisclosed subject matter focuses on decoder operation. The descriptionof encoder technologies can be abbreviated as they are the inverse ofthe comprehensively described decoder technologies. Only in certainareas a more detail description is required and provided below.

During operation, in some examples, the source coder (630) may performmotion compensated predictive coding, which codes an input picturepredictively with reference to one or more previously coded picture fromthe video sequence that were designated as “reference pictures.” In thismanner, the coding engine (632) codes differences between pixel blocksof an input picture and pixel blocks of reference picture(s) that may beselected as prediction reference(s) to the input picture.

The local video decoder (633) may decode coded video data of picturesthat may be designated as reference pictures, based on symbols createdby the source coder (630). Operations of the coding engine (632) mayadvantageously be lossy processes. When the coded video data may bedecoded at a video decoder (not shown in FIG. 6 ), the reconstructedvideo sequence typically may be a replica of the source video sequencewith some errors. The local video decoder (633) replicates decodingprocesses that may be performed by the video decoder on referencepictures and may cause reconstructed reference pictures to be stored inthe reference picture cache (634). In this manner, the video encoder(603) may store copies of reconstructed reference pictures locally thathave common content as the reconstructed reference pictures that will beobtained by a far-end video decoder (absent transmission errors).

The predictor (635) may perform prediction searches for the codingengine (632). That is, for a new picture to be coded, the predictor(635) may search the reference picture memory (634) for sample data (ascandidate reference pixel blocks) or certain metadata such as referencepicture motion vectors, block shapes, and so on, that may serve as anappropriate prediction reference for the new pictures. The predictor(635) may operate on a sample block-by-pixel block basis to findappropriate prediction references. In some cases, as determined bysearch results obtained by the predictor (635), an input picture mayhave prediction references drawn from multiple reference pictures storedin the reference picture memory (634).

The controller (650) may manage coding operations of the source coder(630), including, for example, setting of parameters and subgroupparameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder (645). The entropy coder (645)translates the symbols as generated by the various functional units intoa coded video sequence, by lossless compressing the symbols according totechnologies such as Huffman coding, variable length coding, arithmeticcoding, and so forth.

The transmitter (640) may buffer the coded video sequence(s) as createdby the entropy coder (645) to prepare for transmission via acommunication channel (660), which may be a hardware/software link to astorage device which would store the encoded video data. The transmitter(640) may merge coded video data from the video coder (603) with otherdata to be transmitted, for example, coded audio data and/or ancillarydata streams (sources not shown).

The controller (650) may manage operation of the video encoder (603).During coding, the controller (650) may assign to each coded picture acertain coded picture type, which may affect the coding techniques thatmay be applied to the respective picture. For example, pictures oftenmay be assigned as one of the following picture types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other picture in the sequence as a source ofprediction. Some video codecs allow for different types of intrapictures, including, for example Independent Decoder Refresh (“IDR”)Pictures. A person skilled in the art is aware of those variants of Ipictures and their respective applications and features.

A predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A bi-directionally predictive picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16 sampleseach) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded predictively, viaspatial prediction or via temporal prediction with reference to onepreviously coded reference picture. Blocks of B pictures may be codedpredictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures.

The video encoder (603) may perform coding operations according to apredetermined video coding technology or standard, such as ITU-T Rec.H.265. In its operation, the video encoder (603) may perform variouscompression operations, including predictive coding operations thatexploit temporal and spatial redundancies in the input video sequence.The coded video data, therefore, may conform to a syntax specified bythe video coding technology or standard being used.

In an embodiment, the transmitter (640) may transmit additional datawith the encoded video. The source coder (630) may include such data aspart of the coded video sequence. Additional data may comprisetemporal/spatial/SNR enhancement layers, other forms of redundant datasuch as redundant pictures and slices, SEI messages, VUI parameter setfragments, and so on.

A video may be captured as a plurality of source pictures (videopictures) in a temporal sequence. Intra-picture prediction (oftenabbreviated to intra prediction) makes use of spatial correlation in agiven picture, and inter-picture prediction makes uses of the (temporalor other) correlation between the pictures. In an example, a specificpicture under encoding/decoding, which is referred to as a currentpicture, is partitioned into blocks. When a block in the current pictureis similar to a reference block in a previously coded and still bufferedreference picture in the video, the block in the current picture can becoded by a vector that is referred to as a motion vector. The motionvector points to the reference block in the reference picture, and canhave a third dimension identifying the reference picture, in casemultiple reference pictures are in use.

In some embodiments, a bi-prediction technique can be used in theinter-picture prediction. According to the bi-prediction technique, tworeference pictures, such as a first reference picture and a secondreference picture that are both prior in decoding order to the currentpicture in the video (but may be in the past and future, respectively,in display order) are used. A block in the current picture can be codedby a first motion vector that points to a first reference block in thefirst reference picture, and a second motion vector that points to asecond reference block in the second reference picture. The block can bepredicted by a combination of the first reference block and the secondreference block.

Further, a merge mode technique can be used in the inter-pictureprediction to improve coding efficiency.

According to some embodiments of the disclosure, predictions, such asinter-picture predictions and intra-picture predictions are performed inthe unit of blocks. For example, according to the HEVC standard, apicture in a sequence of video pictures is partitioned into coding treeunits (CTU) for compression, the CTUs in a picture have the same size,such as 64×64 pixels, 32×32 pixels, or 16×16 pixels. In general, a CTUincludes three coding tree blocks (CTBs), which are one luma CTB and twochroma CTBs. Each CTU can be recursively quadtree split into one ormultiple coding units (CUs). For example, a CTU of 64×64 pixels can besplit into one CU of 64×64 pixels, or 4 CUs of 32×32 pixels, or 16 CUsof 16×16 pixels. In an example, each CU is analyzed to determine aprediction type for the CU, such as an inter prediction type or an intraprediction type. The CU is split into one or more prediction units (PUs)depending on the temporal and/or spatial predictability. Generally, eachPU includes a luma prediction block (PB), and two chroma PBs. In anembodiment, a prediction operation in coding (encoding/decoding) isperformed in the unit of a prediction block. Using a luma predictionblock as an example of a prediction block, the prediction block includesa matrix of values (e.g., luma values) for pixels, such as 8×8 pixels,16×16 pixels, 8×16 pixels, 16×8 pixels, and the like.

FIG. 7 shows a diagram of a video encoder (703) according to anotherembodiment of the disclosure. The video encoder (703) is configured toreceive a processing block (e.g., a prediction block) of sample valueswithin a current video picture in a sequence of video pictures, andencode the processing block into a coded picture that is part of a codedvideo sequence. In an example, the video encoder (703) is used in theplace of the video encoder (403) in the FIG. 4 example.

In an HEVC example, the video encoder (703) receives a matrix of samplevalues for a processing block, such as a prediction block of 8×8samples, and the like. The video encoder (703) determines whether theprocessing block is best coded using intra mode, inter mode, orbi-prediction mode using, for example, rate-distortion optimization.When the processing block is to be coded in intra mode, the videoencoder (703) may use an intra prediction technique to encode theprocessing block into the coded picture; and when the processing blockis to be coded in inter mode or bi-prediction mode, the video encoder(703) may use an inter prediction or bi-prediction technique,respectively, to encode the processing block into the coded picture. Incertain video coding technologies, merge mode can be an inter pictureprediction submode where the motion vector is derived from one or moremotion vector predictors without the benefit of a coded motion vectorcomponent outside the predictors. In certain other video codingtechnologies, a motion vector component applicable to the subject blockmay be present. In an example, the video encoder (703) includes othercomponents, such as a mode decision module (not shown) to determine themode of the processing blocks.

In the FIG. 7 example, the video encoder (703) includes the interencoder (730), an intra encoder (722), a residue calculator (723), aswitch (726), a residue encoder (724), a general controller (721), andan entropy encoder (725) coupled together as shown in FIG. 7 .

The inter encoder (730) is configured to receive the samples of thecurrent block (e.g., a processing block), compare the block to one ormore reference blocks in reference pictures (e.g., blocks in previouspictures and later pictures), generate inter prediction information(e.g., description of redundant information according to inter encodingtechnique, motion vectors, merge mode information), and calculate interprediction results (e.g., predicted block) based on the inter predictioninformation using any suitable technique. In some examples, thereference pictures are decoded reference pictures that are decoded basedon the encoded video information.

The intra encoder (722) is configured to receive the samples of thecurrent block (e.g., a processing block), in some cases compare theblock to blocks already coded in the same picture, generate quantizedcoefficients after transform, and in some cases also intra predictioninformation (e.g., an intra prediction direction information accordingto one or more intra encoding techniques). In an example, the intraencoder (722) also calculates intra prediction results (e.g., predictedblock) based on the intra prediction information and reference blocks inthe same picture.

The general controller (721) is configured to determine general controldata and control other components of the video encoder (703) based onthe general control data. In an example, the general controller (721)determines the mode of the block, and provides a control signal to theswitch (726) based on the mode. For example, when the mode is the intramode, the general controller (721) controls the switch (726) to selectthe intra mode result for use by the residue calculator (723), andcontrols the entropy encoder (725) to select the intra predictioninformation and include the intra prediction information in thebitstream; and when the mode is the inter mode, the general controller(721) controls the switch (726) to select the inter prediction resultfor use by the residue calculator (723), and controls the entropyencoder (725) to select the inter prediction information and include theinter prediction information in the bitstream.

The residue calculator (723) is configured to calculate a difference(residue data) between the received block and prediction resultsselected from the intra encoder (722) or the inter encoder (730). Theresidue encoder (724) is configured to operate based on the residue datato encode the residue data to generate the transform coefficients. In anexample, the residue encoder (724) is configured to convert the residuedata from a spatial domain to a frequency domain, and generate thetransform coefficients. The transform coefficients are then subject toquantization processing to obtain quantized transform coefficients. Invarious embodiments, the video encoder (703) also includes a residuedecoder (728). The residue decoder (728) is configured to performinverse-transform, and generate the decoded residue data. The decodedresidue data can be suitably used by the intra encoder (722) and theinter encoder (730). For example, the inter encoder (730) can generatedecoded blocks based on the decoded residue data and inter predictioninformation, and the intra encoder (722) can generate decoded blocksbased on the decoded residue data and the intra prediction information.The decoded blocks are suitably processed to generate decoded picturesand the decoded pictures can be buffered in a memory circuit (not shown)and used as reference pictures in some examples.

The entropy encoder (725) is configured to format the bitstream toinclude the encoded block. The entropy encoder (725) is configured toinclude various information according to a suitable standard, such asthe HEVC standard. In an example, the entropy encoder (725) isconfigured to include the general control data, the selected predictioninformation (e.g., intra prediction information or inter predictioninformation), the residue information, and other suitable information inthe bitstream. Note that, according to the disclosed subject matter,when coding a block in the merge submode of either inter mode orbi-prediction mode, there is no residue information.

FIG. 8 shows a diagram of a video decoder (810) according to anotherembodiment of the disclosure. The video decoder (810) is configured toreceive coded pictures that are part of a coded video sequence, anddecode the coded pictures to generate reconstructed pictures. In anexample, the video decoder (810) is used in the place of the videodecoder (410) in the FIG. 4 example.

In the FIG. 8 example, the video decoder (810) includes an entropydecoder (871), an inter decoder (880), a residue decoder (873), areconstruction module (874), and an intra decoder (872) coupled togetheras shown in FIG. 8 .

The entropy decoder (871) can be configured to reconstruct, from thecoded picture, certain symbols that represent the syntax elements ofwhich the coded picture is made up. Such symbols can include, forexample, the mode in which a block is coded (such as, for example, intramode, inter mode, bi-predicted mode, the latter two in merge submode oranother submode), prediction information (such as, for example, intraprediction information or inter prediction information) that canidentify certain sample or metadata that is used for prediction by theintra decoder (872) or the inter decoder (880), respectively, residualinformation in the form of, for example, quantized transformcoefficients, and the like. In an example, when the prediction mode isinter or bi-predicted mode, the inter prediction information is providedto the inter decoder (880); and when the prediction type is the intraprediction type, the intra prediction information is provided to theintra decoder (872). The residual information can be subject to inversequantization and is provided to the residue decoder (873).

The inter decoder (880) is configured to receive the inter predictioninformation, and generate inter prediction results based on the interprediction information.

The intra decoder (872) is configured to receive the intra predictioninformation, and generate prediction results based on the intraprediction information.

The residue decoder (873) is configured to perform inverse quantizationto extract de-quantized transform coefficients, and process thede-quantized transform coefficients to convert the residual from thefrequency domain to the spatial domain. The residue decoder (873) mayalso require certain control information (to include the QuantizerParameter (QP)), and that information may be provided by the entropydecoder (871) (data path not depicted as this may be low volume controlinformation only).

The reconstruction module (874) is configured to combine, in the spatialdomain, the residual as output by the residue decoder (873) and theprediction results (as output by the inter or intra prediction modulesas the case may be) to form a reconstructed block, that may be part ofthe reconstructed picture, which in turn may be part of thereconstructed video. It is noted that other suitable operations, such asa deblocking operation and the like, can be performed to improve thevisual quality.

It is noted that the video encoders (403), (603), and (703), and thevideo decoders (410), (510), and (810) can be implemented using anysuitable technique. In an embodiment, the video encoders (403), (603),and (703), and the video decoders (410), (510), and (810) can beimplemented using one or more integrated circuits. In anotherembodiment, the video encoders (403), (603), and (603), and the videodecoders (410), (510), and (810) can be implemented using one or moreprocessors that execute software instructions.

Neural network technology can be used with video coding technology, andthe video coding technology with neural network can be referred to ashybrid video coding technology. For example, a loop filter unit, such asthe loop filter unit (556) may apply various loop filters for samplefiltering. One or more of the loop filters can be implemented by neuralnetwork. Aspects of the present disclosure provide techniques of in-loopfiltering in hybrid video coding technologies for improving picturequality using neural network. Specifically, according to an aspect ofthe disclosure, techniques of clipping data can be used before the datais fed to the kernel of a neural network based in loop filter.

According to an aspect of the disclosure, in loop filters are filtersthat influence the reference data. For example, the filtered image bythe loop filter unit (556) is stored in a buffer, such as the referencepicture memory (557) as a reference for further prediction. In loopfilters can improve video quality in a video codec.

FIG. 9 shows a block diagram of a loop filter unit (900) in someexamples. The loop filter unit (900) can be used in the place of theloop filter unit (556) in an example. In the FIG. 9 example, the loopfilter unit (900) includes a deblocking filter (901), a sample adaptiveoffset (SAO) filter (902), and an adaptive loop filter (ALF) filter(903). In some examples, the ALF filter (903) can include crosscomponent adaptive loop filter (CCALF).

During operation, in an example, the loop filter unit (900) receives areconstructed picture, applies various filters on the reconstructedpicture and generates an output picture in response to the reconstructedpicture.

In some examples, the deblocking filter (901) and the SAO filter (902)are configured to remove blocking artifacts that are introduced whenblock coding techniques are used. The deblocking filter (901) can smoothshape edges that are formed when block coding techniques are used. TheSAO filter (902) can apply specific offsets to samples in order toreduce distortion relative to other samples in a video frame. The ALF(903) can apply a classification to, for example, a block of samples,and then apply a filter associated with the classification on the blockof samples. The filter coefficients of the filter can be determined bythe encoder and signaled to the decoder in some examples.

In some examples (e.g., JVET-T0057), an additional filter that isreferred to as a dense residual convolutional neural network basedin-loop filter (DRNLF) can be inserted between the deblocking filter(901) and the SAO filter (902). The DRNLF can further improve picturequality.

FIG. 10 shows a block diagram of a loop filter unit (1000) in someexamples. The loop filter unit (1000) can be used in the place of theloop filter unit (556) in an example. In the FIG. 10 example, the loopfilter unit (1000) includes a deblocking filter (1001), an SAO filter(1002), an ALF filter (1003), and a DRNLF filter (1010) that is placedbetween the deblocking filter (1001) and the SAO filter (1002).

The deblocking filter (1001) is similarly configured as the deblockingfilter (901), the SAO filter (1002) is similarly configured as the SAOfilter (902), and the ALF filter (1003) is similarly configured as theALF filter (903).

The DRNLF filter (1010) receives the output of the deblocking filter(1001) that shown by a deblocked picture (1011) and also receives aquantization parameter (QP) map of reconstructed picture. The QP mapincludes quantization parameters of blocks in the reconstructed picture.The DRNLF filter (1010) can output a picture that is shown by filteredpicture (1019) with improved quality, and the filtered picture (1019) isfed to the SAO filter (1002) for further filtering processes.

According to an aspect of the disclosure, a neural network for videoprocessing can include multiple channels for processing color componentsin a color space. In an example, a color space can be defined usingYCbCr model. In the YCbCr model, Y represents a luma component (thebrightness) and Cb and Cr represent chroma components. It is noted that,in following description, YUV is used to describe format that areencoded using YCbCr model.

According to an aspect of the disclosure, the multiple channels in aneural network are configured to operate on color components of the samesize. In some examples, pictures can be represented by color componentsof different sizes. For example, human visual system is much moresensitive to variations in brightness than color, thus a video systemcan compress the chroma components to reduce file size and savetransmission time without much visual difference as perceived by humaneyes. In some examples, chroma subsampling techniques are used toimplementing less resolution for chroma information than for lumainformation taking advantage of the human visual system's acuity forcolor difference than for luminance.

In some examples, subsampling can be expressed as a three-part ratio,such as 4:4:4, 4:2:0, 4:2:2, 4:1:1 and the like. For example, 4:4:4(also referred to as YUV444) indicates each of the YCbCr components hasthe same sample rate without subsampling; 4:2:0 (also referred to asYUV420) indicates the chroma components are subsampled, every fourpixels (or Y component) can correspond to a Cb component and a Crcomponent. It is noted that YUV420 is used in the following descriptionas an example of subsampling format to illustrate the techniquesdisclosed in the present disclosure. The disclosed techniques can beused for other subsampling format. For ease of description, the format(e.g., YUV444) with color components of the same sample rate withoutsubsampling is referred to as non subsampled format; and the formats(e.g., YUV420, YUV422, YUV411 and the like) with at least one colorcomponent that is subsampled are referred to as subsampled formats.

Generally, a neural network can operate on pictures of the nonsubsampled format (e.g., YUV444). Thus, for a picture of a subsampledformat, the picture is converted into the non subsampled format beforebeing provided as input to the neural network.

FIG. 11 shows a block diagram of a DRNLF filter (1100) in some examples.The DRNLF filter (1100) can be used in the place of the DRNLF filter(1010) in an example. The DRNLF filter (1100) includes a QP mapquantizer (1110), a pre-processing module (1120), a main processingmodule (1130) and a post processing module (1140) coupled together asshown in FIG. 11 . The main processing module (1130) includes a patchfetcher (1131), a patch based DRNLF kernel processing module (1132) anda patch reassembler (1133) coupled together as shown in FIG. 11 .

In some examples, the QP map includes a map of QP values that areapplied to reconstruct respective blocks in the current reconstructedpicture. The QP map quantizer (1110) can quantize the values into a setof pre-determined values. In an example (e.g., JVET-T0057), QP valuescan be quantized by the QP map quantizer (1110) to one of 22, 27, 32,and 37.

The pre-processing module (1120) can receive the deblocked picture in afirst format, and convert to a second format that is used by the mainprocessing module (1130). For example, the main processing module (1130)is configured to process a picture with YUV444 format. When thepre-processing module (1120) receives the deblocked picture in adifferent format from the YUV444 format, the pre-processing module(1120) can process the deblocked picture in the different format, andoutput the deblocked picture in the YUV444 format. For example, thepre-processing module (1120) receives the deblocked picture in YUV420format, and then interpolates the U and V chrominance channelshorizontally and vertically by a factor of 2 to generate the deblockedpicture in YUV444 format.

The main processing module (1130) can receive the deblocked picture inthe YUV444 format and the quantized QP map as inputs. The patch fetcher(1131) disassembles the inputs into patches. The DRNLF kernel processingmodule (1132) can respectively process each of the patches based on theDRNLF kernel. The patch reassembler (1133) can assemble the processedpatches by the DRNLF kernel processing module (1132) into a filteredpicture in the YUV444 format.

The post processing module (1140) coverts the filtered picture in thesecond format back to the first format. For example, the post processingmodule (1140) receives the filtered picture in the YUV444 format (outputfrom the main processing module (1130)) and outputs the filtered picturein the YUV420 format.

FIG. 12 shows a block diagram of a pre-processing module (1220) in someexamples. In an example, the pre-processing module (1220) is used in theplace of the pre-processing module (1120).

The pre-processing module (1220) can receive deblocked picture in YUV420format, convert the deblocked picture into YUV444 format and output thedeblocked picture in the YUV444 format. Specifically, the pre-processingmodule (1220) receives the deblocked picture in three input channelsthat include a luminance input channel for Y component, and twochrominance input channels respectively for U(Cb) component and V(Cr)components. The pre-processing module (1220) outputs the deblockedpicture by three output channels that include a luminance output channelfor Y component, and two chrominance output channels respectively forthe U(Cb) component and V(Cr) component.

In an example, when the deblocked picture has the YUV420 format, the Ycomponent has a size (H, W), the U component has a size (H/2, W/2) andthe V component has a size (H/2, W/2), where H denotes the height (e.g.,in the unit of samples) of the deblocked picture and W denotes the width(e.g., in the unit of samples) of the deblocked picture.

In the FIG. 12 example, the pre-processing module (1220) does not resizethe Y component. The pre-processing module (1220) receives the Ycomponent with the size (H, W) from the luminance input channel andoutputs the Y component with size (H, W) to the luminance outputchannel.

The pre-processing module (1220) respectively resizes the U componentand the V component. The pre-processing module (1220) includes a firstresize unit (1221) and a second resize unit (1222) to process the Ucomponent and V component respectively. For example, the first resizeunit (1221) receives the U component with the size (H/2, W/2), resizesthe U component to the size (H, W), and outputs the U component with thesize (H, W) to the chrominance output channel for the U component. Thesecond resize unit (1222) receives the V component with the size (H/2,W/2), resizes the V component to the size (H, W), and outputs the Vcomponent with the size (H, W) to the chrominance output channel for theV component. In some examples, the first resize unit (1221) resizes theU component based on interpolation, such as using a Lanczosinterpolation filter. Similarly, in some examples, the second resizeunit (1222) resizes the V component based on interpolation, such asusing a Lanczos interpolation filter.

In some examples, interpolation operations, such as using the Lanczosinterpolation filter and the like, cannot guarantee that the output ofthe interpolation operations to be meaningful values, such as to benon-negative for meaningful U(Cb) component and V(Cr) component. In someexamples, the deblocked pictures in the YUV444 format after thepre-processing can be stored and then the stored pictures in the YUV444format can be used in a training process of a neural network. Thenegative values of U(Cb) component and V(Cr) component can adverselyaffect the results of the training process of the neural network.

FIG. 13 shows a block diagram of a neural network structure (1300). Insome examples, the neural network structure (1300) is used for a denseresidual convolutional neural network based in-loop filter (DRNLF), andcan be used in the place of the patch based DRNLF kernel processingmodule (1132). The neural network structure (1300) includes a series ofdense residual units (DRUs), such as DRU (1301)-DRU (1304), and thenumber of DRUs is denoted by N. In FIG. 13 , the number of convolutionkernel is denoted by M and M is also the number of output channels forconvolution. For example, “CONV 3×3×M” indicates standard convolutionwith M convolution kernels of the kernel size 3×3, “DSC 3×3×M” indicatesdepthwise separable convolution with M convolution kernels of kernelsize 3×3. N and M can be set for the tradeoff between computationalefficiency and performance. In an example (e.g., JVET-T0057), N is setto 4 and M is set to 32.

During operation, the neural network structure (1300) processes thedeblocked picture by patch. For each patch of the deblocked picture inthe YUV444 format, the patch is normalized (e.g., divided by 1023 inFIG. 13 example), and the mean value of the deblocked picture is removedfrom the normalized patch to obtain a first portion (1311) of aninternal input (1313). The second portion of the internal input (1313)is from the QP map. For example, a patch of the QP map (referred to asQP map patch) corresponding to the patch that forms the first portion(1311) is obtained from the QP map. The QP map patch is normalized(e.g., divided by 51 in FIG. 13 ). The normalized QP map patch is thesecond portion (1312) of the internal input (1313). The second portion(1312) is concatenated with the first portion (1311) to obtain theinternal input (1313). The internal input (1313) is provided to a firstregular convolution block (1351) (shown by CONV 3×3×M). The output ofthe first regular convolution block (1351) is then processed by N DRUs.

For each DRU, an intermediate input is received and processed. Theoutput of the DRU is concatenated with the intermediate input to form anintermediate input for a next DRU. Using the DRU (1302) as an example,the DRU (1302) receives an intermediate input (1321), processes theintermediate input (1321) and generates an output (1322). The output(1322) is concatenated with the intermediate input (1321) to form anintermediate input (1323) for the DRU (1303).

It is noted, due to the reason that the intermediate input (1321) hasmore than M channels, a convolution operation of “CONV 1×1×M” can beapplied to the intermediate input (1321) to generate M channels forfurther processing by the DRU(1302). It is also noted that the output ofthe first regular convolution block (1351) includes M channels, thus theoutput can be processed by the DRU (1301) without using the convolutionoperation of “CONV 1×1×M”.

The output of the last DRU is provided to a last regular convolutionblock (1359). The output of the last regular convolution block (1359) isconverted to regular picture patch values, for example by adding themean value of the deblocked picture, and multiplying 1023 as shown inFIG. 13 .

FIG. 14 shows a block diagram of a dense residual unit (DRU) (1400). Insome examples, the DRU (1400) can be used in the place of each of theDRUs in FIG. 13 , such as DRU (1301), DRU (1302), DRU (1303) and DRU(1304).

In the FIG. 14 example, the DRU (1400) receives an intermediate input x,and directly propagates the intermediate input to a subsequent DRUthrough a shortcut (1401). The DRU (1400) also includes a regularprocessing path (1402). In some examples, the regular processing path(1402) includes a regular convolution layer (1411), depthwise separableconvolution (DSC) layers (1412) and (1414), and a rectified linear unit(ReLU) layer (1413). For example, the intermediate input x isconcatenated with output of the regular processing path (1402) to forman intermediate input for the subsequent DRU.

In some examples, the DSC layers (1412) and (1414) are used to reducethe computational cost.

According to an aspect of the disclosure, the neural network structure(1300) includes three channels corresponding to the Y, U(Cb), V(Cr)components, respectively. The three channels can be referred to as Ychannel, U channel and V channel in some examples. The DRNLF filter(1100) can be applied to both intra and inter pictures. In someexamples, additional flags are signaled to indicate the on/off of theDRNLF filter (1100) at picture level and CTU level.

FIG. 15 shows a block diagram of a post processing module (1540) in someexamples. The post processing module (1540) can be used in the place ofthe post processing module (1140) in an example. The post processingmodule (1540) includes clip units (1541)-(1543) that respectively clipthe values of the Y component, U component and V component intopre-determined non-negative range [a, b]. In an example, the lower limita and the upper limit b of the non-negative range can be set as a=16×4and b=234×4. Further, the post processing module (1540) includes resizeunits (1545) and (1546) that respectively resize the clipped U componentand V component from size (H, W) to size (H/2, W/2), where H is theheight and W is the width of the original picture (e.g., deblockedpicture).

Aspects of the present disclosure provide techniques of pre-processing.The pre-processed data can be stored and used for training of neuralnetwork, and get better training and inference results.

FIG. 16 shows a block diagram of a pre-processing module (1620) in someexamples. In an example, the pre-processing module (1620) is used in theplace of the pre-processing module (1120).

The pre-processing module (1620) can receive deblocked picture in YUV420format, convert the deblocked picture into YUV444 format and output thedeblocked picture in the YUV444 format. Specifically, the pre-processingmodule (1620) receives the deblocked picture in three input channelsthat include a luminance input channel for Y component, and twochrominance input channels respectively for U(Cb) component and V(Cr)components. The pre-processing module (1620) outputs the deblockedpicture by three output channels that include a luminance output channelfor Y component, and two chrominance output channels respectively forthe U component and V component.

In an example, when the deblocked picture has the YUV420 format, the Ycomponent has a size (H, W), the U component has a size (H/2, W/2) andthe V component has a size (H/2, W/2), where H denotes the height (e.g.,in the unit of samples) of the deblocked picture and W denotes the width(e.g., in the unit of samples) of the deblocked picture.

In the FIG. 16 example, the pre-processing module (1620) does not resizethe Y component. The pre-processing module (1620) receives the Ycomponent with the size (H, W) from the luminance input channel andoutputs the Y component with size (H, W) to the luminance outputchannel.

The pre-processing module (1620) respectively resizes the U componentand the V component. The pre-processing module (1620) includes a firstresize unit (1621) and a second resize unit (1622) to process the Ucomponent and V component respectively. For example, the first resizeunit (1621) receives the U component with the size (H/2, W/2), resizesthe U component to the size (H, W), and outputs the U component with thesize (H, W) to the chrominance output channel for the U component. Thesecond resize unit (1622) receives the V component with the size (H/2,W/2), resizes the V component to the size (H, W), and outputs the Vcomponent with the size (H, W) to the chrominance output channel for theV component. In some examples, the first resize unit (1621) resizes theU component based on interpolation, such as using a Lanczosinterpolation filter. Similarly, in some examples, the second resizeunit (1622) resizes the V component based on interpolation, such asusing a Lanczos interpolation filter.

In some examples, interpolation operations, such as using the Lanczosinterpolation filter and the like, cannot guarantee that the output ofthe interpolation operations to be meaningful values, such as to benon-negative for meaningful U(Cb) component and V(Cr) component.

In the FIG. 16 example, the pre-processing module (1620) includes clipunits (1625) and (1626) to respectively clip values of U component and Vcomponent after interpolation into a range of [c, d]. In some examples,values of Y component, U component and V component for pre-processinghave a bitdepth of 10, then c and d can be set as c=0 andd=2^(bitdepth)−1=1023.

In an example, c and d values are predefined and used. In anotherexample, multiple pairs of c and d values are predefined, and index ofthe pair of c and d values for use in the clipping can be signaled inthe bitstream, such as in sequence parameter set (SPS), pictureparameter set (PPS), slice or tile header.

In some examples, the clipped values of the U component and V componentand the values of the Y component can be stored as the deblocked picturein the YUV444 format. In some embodiments, the stored pictures in theYUV444 format can be used as inputs in a training process of a neuralnetwork, such as the neural network in the main processing module(1130). In some examples, the values of U and V components are clippedin a range that will not adversely affect the training process of theneural network. In an example, the values of U and V components areclipped to be non-negative.

In some examples, using pictures stored in the YUV444 format with theclipped values, the training of the neural network can be speedup due totime saving by avoiding the pre-processing (e.g., resizing, clipping)step during training. Additionally, the neural network can be trainedwith better model parameters that can improve compression efficiencyand/or picture quality.

In some examples, adding the clipping units (1625) and (1626) in thepre-processing module (1620) can improve compression efficiency and/orquality, for example with lower Bjontegaard delta rate (BD-rate).

FIG. 17 shows a flow chart outlining a process (1700) according to anembodiment of the disclosure. The process (1700) can be used in videoprocessing. In various embodiments, the process (1700) are executed byprocessing circuitry, such as the processing circuitry in the terminaldevices (310), (320), (330) and (340), the processing circuitry thatperforms functions of the video encoder (403), the processing circuitrythat performs functions of the video decoder (410), the processingcircuitry that performs functions of the video decoder (510), theprocessing circuitry that performs functions of the video encoder (603),and the like. In some embodiments, the process (1700) is implemented insoftware instructions, thus when the processing circuitry executes thesoftware instructions, the processing circuitry performs the process(1700). The process starts at (S1701) and proceeds to (S1710).

At (S1710), a picture in a sub sampled format in a color space isconverted into a non subsampled format in the color space. In someexamples, the conversion is performed based on interpolation, and mayresult invalid values. In an example, the conversion may result negativevalues that are not valid for YCbCr model.

At (S1720), values of one of more color components of the picture in thenon subsampled format are clipped before the picture in the nonsubsampled format is provided as an input to a neural network basedfilter. In some examples, the one or more color components can be chromacomponent(s). Then, the process proceeds to (S1799).

In an example, the values of the color component of the picture in thenon subsampled format are clipped into a valid range for the colorcomponent. In an example, the values of the color component of thepicture in the non subsampled format are clipped to be non negative. Inanother example, a range that is determined based on a bitdepth. Forexample, the lower limit of the range is 0, and the upper limit of therange is set to (2^(bitdepth))−1.

In some examples, the range is predetermined. In some examples, therange is determined based on decoded information from a bitstream thatcarries the picture. In some examples, a signal that is indicative ofthe range is decode, from at least one of a sequence parameter set, apicture parameter set, a slice header and a tile header in thebitstream.

In example, multiple ranges can be pre-determined. Then, an index thatis indicative of one of the multiple ranges can be carried in one of asequence parameter set, a picture parameter set, a slice header and atile header in the bitstream.

In some examples, the process (1700) is used in a decoder. For example,the picture in the subsampled format is reconstructed based on decodedinformation from a bitstream, and a deblocking filter is applied on thepicture in the subsampled format before the conversion from thesubsampled format to the non sub sampled format. In another example, theneural network based filter is applied on the picture in the nonsubsampled format with the clipped values to generate a filtered pictureof the non subsampled format, and then the filtered picture in the nonsubsampled format is converted to a filtered picture of the sub sampledformat.

In some examples, the picture in the non subsampled format with theclipped values is stored in a storage. Then, the stored picture in thenon subsampled format with the clipped values can be provided with otherpictures as a training input to train a neural network in the neuralnetwork based filter.

It is noted that various units, blocks and modules in the abovedescription can be implemented by various technology, such as,processing circuitry, processor executing software instructions, acombination of hardware and software, and the like.

The techniques described above, can be implemented as computer softwareusing computer-readable instructions and physically stored in one ormore computer-readable media. For example, FIG. 18 shows a computersystem (1800) suitable for implementing certain embodiments of thedisclosed subject matter.

The computer software can be coded using any suitable machine code orcomputer language, that may be subject to assembly, compilation,linking, or like mechanisms to create code comprising instructions thatcan be executed directly, or through interpretation, micro-codeexecution, and the like, by one or more computer central processingunits (CPUs), Graphics Processing Units (GPUs), and the like.

The instructions can be executed on various types of computers orcomponents thereof, including, for example, personal computers, tabletcomputers, servers, smartphones, gaming devices, internet of thingsdevices, and the like.

The components shown in FIG. 18 for computer system (1800) are exemplaryin nature and are not intended to suggest any limitation as to the scopeof use or functionality of the computer software implementingembodiments of the present disclosure. Neither should the configurationof components be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary embodiment of a computer system (1800).

Computer system (1800) may include certain human interface inputdevices. Such a human interface input device may be responsive to inputby one or more human users through, for example, tactile input (such as:keystrokes, swipes, data glove movements), audio input (such as: voice,clapping), visual input (such as: gestures), olfactory input (notdepicted). The human interface devices can also be used to capturecertain media not necessarily directly related to conscious input by ahuman, such as audio (such as: speech, music, ambient sound), images(such as: scanned images, photographic images obtain from a still imagecamera), video (such as two-dimensional video, three-dimensional videoincluding stereoscopic video).

Input human interface devices may include one or more of (only one ofeach depicted): keyboard (1801), mouse (1802), trackpad (1803), touchscreen (1810), data-glove (not shown), joystick (1805), microphone(1806), scanner (1807), camera (1808).

Computer system (1800) may also include certain human interface outputdevices. Such human interface output devices may be stimulating thesenses of one or more human users through, for example, tactile output,sound, light, and smell/taste. Such human interface output devices mayinclude tactile output devices (for example tactile feedback by thetouch-screen (1810), data-glove (not shown), or joystick (1805), butthere can also be tactile feedback devices that do not serve as inputdevices), audio output devices (such as: speakers (1809), headphones(not depicted)), visual output devices (such as screens (1810) toinclude CRT screens, LCD screens, plasma screens, OLED screens, eachwith or without touch-screen input capability, each with or withouttactile feedback capability—some of which may be capable to output twodimensional visual output or more than three dimensional output throughmeans such as stereographic output; virtual-reality glasses (notdepicted), holographic displays and smoke tanks (not depicted)), andprinters (not depicted).

Computer system (1800) can also include human accessible storage devicesand their associated media such as optical media including CD/DVD ROM/RW(1820) with CD/DVD or the like media (1821), thumb-drive (1822),removable hard drive or solid state drive (1823), legacy magnetic mediasuch as tape and floppy disc (not depicted), specialized ROM/ASIC/PLDbased devices such as security dongles (not depicted), and the like.

Those skilled in the art should also understand that term “computerreadable media” as used in connection with the presently disclosedsubject matter does not encompass transmission media, carrier waves, orother transitory signals.

Computer system (1800) can also include an interface (1854) to one ormore communication networks (1855). Networks can for example bewireless, wireline, optical. Networks can further be local, wide-area,metropolitan, vehicular and industrial, real-time, delay-tolerant, andso on. Examples of networks include local area networks such asEthernet, wireless LANs, cellular networks to include GSM, 3G, 4G, 5G,LTE and the like, TV wireline or wireless wide area digital networks toinclude cable TV, satellite TV, and terrestrial broadcast TV, vehicularand industrial to include CANBus, and so forth. Certain networkscommonly require external network interface adapters that attached tocertain general purpose data ports or peripheral buses (1849) (such as,for example USB ports of the computer system (1800)); others arecommonly integrated into the core of the computer system (1800) byattachment to a system bus as described below (for example Ethernetinterface into a PC computer system or cellular network interface into asmartphone computer system). Using any of these networks, computersystem (1800) can communicate with other entities. Such communicationcan be uni-directional, receive only (for example, broadcast TV),uni-directional send-only (for example CANbus to certain CANbusdevices), or bi-directional, for example to other computer systems usinglocal or wide area digital networks. Certain protocols and protocolstacks can be used on each of those networks and network interfaces asdescribed above.

Aforementioned human interface devices, human-accessible storagedevices, and network interfaces can be attached to a core (1840) of thecomputer system (1800).

The core (1840) can include one or more Central Processing Units (CPU)(1841), Graphics Processing Units (GPU) (1842), specialized programmableprocessing units in the form of Field Programmable Gate Areas (FPGA)(1843), hardware accelerators for certain tasks (1844), graphicsadapters (1850), and so forth. These devices, along with Read-onlymemory (ROM) (1845), Random-access memory (1846), internal mass storagesuch as internal non-user accessible hard drives, SSDs, and the like(1847), may be connected through a system bus (1848). In some computersystems, the system bus (1848) can be accessible in the form of one ormore physical plugs to enable extensions by additional CPUs, GPU, andthe like. The peripheral devices can be attached either directly to thecore's system bus (1848), or through a peripheral bus (1849). In anexample, the screen (1810) can be connected to the graphics adapter(1850). Architectures for a peripheral bus include PCI, USB, and thelike.

CPUs (1841), GPUs (1842), FPGAs (1843), and accelerators (1844) canexecute certain instructions that, in combination, can make up theaforementioned computer code. That computer code can be stored in ROM(1845) or RAM (1846). Transitional data can be also be stored in RAM(1846), whereas permanent data can be stored for example, in theinternal mass storage (1847). Fast storage and retrieve to any of thememory devices can be enabled through the use of cache memory, that canbe closely associated with one or more CPU (1841), GPU (1842), massstorage (1847), ROM (1845), RAM (1846), and the like.

The computer readable media can have computer code thereon forperforming various computer-implemented operations. The media andcomputer code can be those specially designed and constructed for thepurposes of the present disclosure, or they can be of the kind wellknown and available to those having skill in the computer software arts.

As an example and not by way of limitation, the computer system havingarchitecture (1800), and specifically the core (1840) can providefunctionality as a result of processor(s) (including CPUs, GPUs, FPGA,accelerators, and the like) executing software embodied in one or moretangible, computer-readable media. Such computer-readable media can bemedia associated with user-accessible mass storage as introduced above,as well as certain storage of the core (1840) that are of non-transitorynature, such as core-internal mass storage (1847) or ROM (1845). Thesoftware implementing various embodiments of the present disclosure canbe stored in such devices and executed by core (1840). Acomputer-readable medium can include one or more memory devices orchips, according to particular needs. The software can cause the core(1840) and specifically the processors therein (including CPU, GPU,FPGA, and the like) to execute particular processes or particular partsof particular processes described herein, including defining datastructures stored in RAM (1846) and modifying such data structuresaccording to the processes defined by the software. In addition or as analternative, the computer system can provide functionality as a resultof logic hardwired or otherwise embodied in a circuit (for example:accelerator (1844)), which can operate in place of or together withsoftware to execute particular processes or particular parts ofparticular processes described herein. Reference to software canencompass logic, and vice versa, where appropriate. Reference to acomputer-readable media can encompass a circuit (such as an integratedcircuit (IC)) storing software for execution, a circuit embodying logicfor execution, or both, where appropriate. The present disclosureencompasses any suitable combination of hardware and software.

Appendix A: Acronyms

-   -   JEM: joint exploration model    -   VVC: versatile video coding    -   BMS: benchmark set    -   MV: Motion Vector    -   HEVC: High Efficiency Video Coding    -   SEI: Supplementary Enhancement Information    -   VUI: Video Usability Information    -   GOPs: Groups of Pictures    -   TUs: Transform Units,    -   PUs: Prediction Units    -   CTUs: Coding Tree Units    -   CTBs: Coding Tree Blocks    -   PBs: Prediction Blocks    -   HRD: Hypothetical Reference Decoder    -   SNR: Signal Noise Ratio    -   CPUs: Central Processing Units    -   GPUs: Graphics Processing Units    -   CRT: Cathode Ray Tube    -   LCD: Liquid-Crystal Display    -   OLED: Organic Light-Emitting Diode    -   CD: Compact Disc    -   DVD: Digital Video Disc    -   ROM: Read-Only Memory    -   RAM: Random Access Memory    -   ASIC: Application-Specific Integrated Circuit    -   PLD: Programmable Logic Device    -   LAN: Local Area Network    -   GSM: Global System for Mobile communications    -   LTE: Long-Term Evolution    -   CANBus: Controller Area Network Bus    -   USB: Universal Serial Bus    -   PCI: Peripheral Component Interconnect    -   FPGA: Field Programmable Gate Areas    -   SSD: solid-state drive    -   IC: Integrated Circuit    -   CU: Coding Unit

While this disclosure has described several exemplary embodiments, thereare alterations, permutations, and various substitute equivalents, whichfall within the scope of the disclosure. It will thus be appreciatedthat those skilled in the art will be able to devise numerous systemsand methods which, although not explicitly shown or described herein,embody the principles of the disclosure and are thus within the spiritand scope thereof.

What is claimed is:
 1. A method of video processing, comprising: converting, by a pre-processing unit of a dense residual convolutional neural network based in-loop filter (DRNLF) in processing circuitry, a picture in a subsampled format in a color space into a non subsampled format in the color space; and clipping, by the pre-processing unit in the processing circuitry, values of only a subset of color components of the picture in the non subsampled format before providing the picture in the non subsampled format as an input to a neural network based filter of the DRNLF.
 2. The method of claim 1, further comprising: clipping the values of each of the subset of color components of the picture in the non subsampled format into a valid range for the respective color component.
 3. The method of claim 1, further comprising: clipping the values of the subset of color components of the picture in the non subsampled format into a range that is determined based on a bitdepth.
 4. The method of claim 1, further comprising: clipping the values of the subset of color components of the picture in the non subsampled format into a range that is predetermined.
 5. The method of claim 1, further comprising: determining a range for clipping the values based on decoded information from a bitstream that carries the picture; and clipping the values of the subset of color components of the picture in the non subsampled format into the determined range.
 6. The method of claim 5, further comprising: decoding, from at least one of a sequence parameter set, a picture parameter set, a slice header and a tile header in the bitstream, a signal that is indicative of the range.
 7. The method of claim 1, further comprising: reconstructing the picture in the subsampled format based on decoded information from a bitstream.
 8. The method of claim 1, further comprising: applying the neural network based filter on the picture in the non subsampled format with the clipped values to generate a filtered picture of the non subsampled format; and converting the filtered picture in the non subsampled format to a filtered picture of the subsampled format.
 9. The method of claim 1, further comprising: storing the picture in the non subsampled format with the clipped values.
 10. The method of claim 9, further comprising: providing the stored picture in the non subsampled format with the clipped values as a training input to train a neural network in the neural network based filter.
 11. An apparatus for video processing, comprising: processing circuitry including a pre-processing unit of a dense residual convolutional neural network based in-loop filter (DRNLF), the pre-processing unit being configured to: convert a picture in a subsampled format in a color space into a non subsampled format in the color space; and clip values of only a subset of color components of the picture in the non subsampled format before providing the picture in the non subsampled format as an input to a neural network based filter of the DRNLF.
 12. The apparatus of claim 11, wherein the processing circuitry is configured to: clip the values of each of the subset of color components of the picture in the non subsampled format into a valid range for the respective color component.
 13. The apparatus of claim 11, wherein the processing circuitry is configured to: clip the values of the subset of color components of the picture in the non subsampled format into a range that is determined based on a bitdepth.
 14. The apparatus of claim 11, wherein the processing circuitry is configured to: clip the values of the subset of color components of the picture in the non subsampled format into a range that is predetermined.
 15. The apparatus of claim 11, wherein the processing circuitry is configured to: determine a range for clipping the values based on decoded information from a bitstream that carries the picture; and clip the values of the color component of the picture in the non subsampled format into the determined range.
 16. The apparatus of claim 15, wherein the processing circuitry is configured to: decode, from at least one of a sequence parameter set, a picture parameter set, a slice header and a tile header in the bitstream, a signal that is indicative of the range.
 17. The apparatus of claim 11, wherein the processing circuitry is configured to: reconstruct the picture in the subsampled format based on decoded information from a bitstream.
 18. The apparatus of claim 11, wherein the processing circuitry is configured to: apply the neural network based filter on the picture in the non subsampled format with the clipped values to generate a filtered picture of the non subsampled format; and convert the filtered picture in the non subsampled format to a filtered picture of the sub sampled format.
 19. The apparatus of claim 11, further comprising: a storage configured to store the picture in the non subsampled format with the clipped values.
 20. The apparatus of claim 19, wherein the processing circuitry is configured to: provide the stored picture in the non subsampled format with the clipped values as a training input to train a neural network in the neural network based filter. 